The characterization of tumors after being imaged is currently a qualitative process performed by skilled professionals. If we can aid their diagnosis by identifying quantifiable features associated with tumor classification, we may avoid invasive procedures such as biopsies and enhance efficiency. The aim of this paper is to describe the 3D EdgeRunner Pipeline which characterizes the shape of a tumor. Shape analysis is relevant as malignant tumors tend to be more lobular and benign ones tare generally more symmetrical. The method described considers the distance from each point on the edge of the tumor to the centre of a synthetically created field of view. The method then determines coordinates where the measured distances are rapidly changing (peaks) using a second derivative found by five point differentiation. The list of coordinates considered to be peaks can then be used as statistical data to compare tumors quantitatively. We have found this process effectively captures the peaks on a selection of kidney tumors.
Sickle cell disease (SCD) is an inherited blood disorder that effects red blood cells, which can lead to vasoocclusion, ischemia and infarct. This disease often results in neurological damage and strokes, leading to morbidity and mortality. Functional Magnetic Resonance Imaging (fMRI) is a non-invasive technique for measuring and mapping the brain activity. Blood Oxygenation Level-Dependent (BOLD) signals contain also information about the neurovascular coupling, vascular reactivity, oxygenation and blood propagation. Temporal relationship between BOLD fluctuations in different parts of the brain provides also a mean to investigate the blood delay information. We used the induced desaturation as a label to profile transit times through different brain areas, reflecting oxygen utilization of tissue. In this study, we aimed to compare blood flow propagation delay times between these patients and healthy subjects in areas vascularized by anterior, middle and posterior cerebral arteries. In a group comparison analysis with control subjects, BOLD changes in these areas were found to be almost simultaneous and shorter in the SCD patients, because of their increased brain blood flow. Secondly, the analysis of a patient with a stenosis on the anterior cerebral artery indicated that signal of the area vascularized by this artery lagged the MCA signal. These findings suggest that sickle cell disease causes blood propagation modifications, and that these changes could be used as a biomarker of vascular damage.
Sickle cell disease (SCD) is a hereditary blood disorder in which the oxygen-carrying hemoglobin molecule in red blood cells is abnormal. It affects numerous people in the world and leads to a shorter life span, pain, anemia, serious infections and neurocognitive decline. Tract-Specific Analysis (TSA) is a statistical method to evaluate white matter alterations due to neurocognitive diseases, using diffusion tensor magnetic resonance images. Here, for the first time, TSA is used to compare 11 major brain white matter (WM) tracts between SCD patients and age-matched healthy subjects. Alterations are found in the corpus callosum (CC), the cortico-spinal tract (CST), inferior fronto-occipital fasciculus (IFO), inferior longitudinal fasciculus (ILF), superior longitudinal fasciculus (SLF), and uncinated fasciculus (UNC). Based on previous studies on the neurocognitive functions of these tracts, the significant areas found in this paper might be related to several cognitive impairments and depression, both of which are observed in SCD patients.
Sickle cell disease may result in neurological damage and strokes, leading to morbidity and mortality. Currently, there are no dependable biomarkers to predict impending strokes. In this study, we analyzed neuronal processes at resting state and more particularly how this disease affects the default mode network. The amplitude of low frequency fluctuations was used to reflect areas of spontaneous BOLD signal across brain regions. We compared the activations of sickle cell disease patients to a control group using variance analysis and t-test. Significant regional differences among the two groups were observed, especially in the default mode network areas and cortical regions near large cerebral arteries. These findings suggest that sickle cell disease causes activation modifications near vessels, and these changes could be used as a biomarker of the disease.